Current solutions for personalizing business websites content according to user profiles are implemented for business websites, which are targeted for consumers. However, the personalization of business websites content is enabled only for identified users that are adapting the shopping content and sale's promotion, according to known preferences and activity of the user.
Known in the art Real-time website personalization is using simple click stream data that exist on the browser level or e-commerce product catalog which is small scale data. In B2B the challenge is to be able to map relevant content to visitors based on business relevancy and stage in the sales cycle, the known solutions enable only “rule-based” personalization only for known users. It is the object of the present invention to detect anonymous users and engage content utilizing predictive analytics in real-time using big data processing.